Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A statistical method to uncover gene expression changes in spatial transcriptomics

Cell type-specific inference of differential expression (C-SIDE) is a statistical model that identifies which genes (within a determined cell type) are differentially expressed on the basis of spatial position, pathological changes or cell–cell interactions. C-SIDE facilitates differential expression analysis in spatial transcriptomics by jointly modeling cell type mixtures and spatially varying gene expression.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: C-SIDE accurately learns cell type-specific DE from spatial transcriptomics data.

References

  1. Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 6434, 1463–1467 (2019). Slide-seq is a high-resolution sequencing-based spatial transcriptomics technology using spatially indexed measurement beads.

    Article  Google Scholar 

  2. Chen, K. H. et al. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348 (2015). MERFISH is an imaging-based spatial transcriptomics technology that profiles gene expression at subcellular resolution.

  3. 10x Genomics. 10x Genomics: Visium spatial gene expression (2020); https://pages.10xgenomics.com/rs/446-PBO-704/images/10x_LIT059_RevC_ProductSheet_VisiumSpatialGeneExpression_Letter_digital.pdf. Visium is a commercially available sequencing-based spatial transcriptomics technology for fixed tissue.

  4. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). DESeq2 is a statistical method for differential expression in RNA-sequencing.

    Article  Google Scholar 

  5. Cable, D. M. et al. Robust decomposition of cell type mixtures in spatial transcriptomics. Nat. Biotechnol. 40, 517–526 (2022). RCTD is a statistical method for identifying cell types in spatial transcriptomics, accounting for cell type mixtures.

    Article  CAS  Google Scholar 

Download references

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a summary of: Cable, D. M. et al. Cell type-specific inference of differential expression in spatial transcriptomics. Nat. Methods https://doi.org/10.1038/s41592-022-01575-3 (2022).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

A statistical method to uncover gene expression changes in spatial transcriptomics. Nat Methods 19, 1046–1047 (2022). https://doi.org/10.1038/s41592-022-01576-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-022-01576-2

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing